Project Summary Atrial fibrillation (AF) is the most common arrhythmia encountered in practice. This cardiac arrhythmia can be sporadic in occurrence and varies in frequency and duration among individuals. However, AF that remains undetected and untreated can result in a poor quality of life, hospitalization, stroke, and death. New, easy to use mobile health (mHealth) methods for detecting AF in the community are needed to facilitate timely detection and treatments aimed at better symptom and clinical management and ultimately improved outcomes. mHealth is a promising platform for self-management of diseases like AF because of the widespread use of mobile technologies, especially among minorities, and the sophistication of mobile electrocardiogram (ECG) software that allows users to record and transmit ECGs to distinguish between a normal rhythm and AF. However, longitudinal data indicates that mHealth use declines over time. Little is known about factors that are associated with sustained engagement with mHealth, yet it is important to understand these factors to optimize the efficacy of mHealth through increased adherence. This has the potential to improve the health outcomes of those living AF. Preliminary studies suggest that individual user characteristics, such as age and disease status, may play a role in sustained engagement; however, this concept has not been thoroughly explored. We aim to take a personalized approach to understanding factors associated with sustained engagement with ECG mHealth technology. In this mixed-methods study, we plan to use participants enrolled in the iHEART trial, an ongoing NINR-supported randomized controlled trial of individuals with AF. We will focus on participants randomized to the iHEART intervention because they will use ECG mHealth technology for six months. Sustained engagement in this study is voluntary use of the ECG mHealth technology per iHEART protocol (at least twice daily for six months). iHEART research coordinators prompt participants to transmit ECGs when forgotten for one week. Preliminary data indicates that approximately half of iHEART participants are not engaged because they require weekly prompting. We will test differences in trajectories of ECG mHealth technology use over the six-month period between engaged and unengaged users using individual growth models. Predictors and moderators of sustained engagement will come from an adapted model of technology acceptance and use that uses and accounts for unique user characteristics, and can be measured using ECG and survey data collected during the iHEART trial. We will conduct focus groups with the iHEART mHealth ECG participants (intervention group) to gain deeper insight into these factors from the user perspective. This project has the potential to provide valuable insight on factors that are associated with mHealth engagement in a high risk AF population.